Robust Remote Estimation Over Shared Networks in the Presence of Denial-of-Service Attacks

Networked multiagent systems often communicate information over low-power shared wireless networks in unlicensed spectrum, which are prone to denial-of-service attacks. An instance of this scenario is considered: multiple pairs of agents, each pair consisting of a transmitting sensor and a receiver acting as an estimator, communicate strategically over shared communication networks in the presence of a jammer who may launch a denial-of-service attack in the form of packet collisions. Using the so-called coordinator approach, we cast this problem as a zero-sum game between the coordinator, who jointly optimizes the transmission and estimation policies, and a jammer, who optimizes its probability of performing an attack. We consider two cases: point-to-point channels and large-scale networks with a countably infinite number of sensor-receiver pairs. When the jammer proactively attacks the channel, we find that this game is nonconvex from the coordinator's perspective. However, we construct a saddle point equilibrium solution for any multivariate Gaussian input distribution for the observations despite the lack of convexity. In the case where the jammer is reactive, we obtain a customized algorithm based on sequential convex optimization, which converges swiftly to first-order Nash equilibria. Interestingly, we discovered that when the jammer is reactive, it is often optimal to block the channel even when it knows that the channel is idle to create ambiguity at the receiver.